Meiqin Yang1, Zhensheng Zhai2, Yunfeng Zhang1, Yue Wang3. 1. Department of Gynecology and Obstetrics, People's Hospital of Zhengzhou University, Henan Provincial People's Hospital, No. 7 Weiwu Road, Jinshui District, Zhengzhou, 450000, Henan, China. 2. Department of Hepato-Biliary-Pancreatic Surgery, People's Hospital of Zhengzhou University, Henan Provincial People's Hospital, Zhengzhou, 450000, Henan, China. 3. Department of Gynecology and Obstetrics, People's Hospital of Zhengzhou University, Henan Provincial People's Hospital, No. 7 Weiwu Road, Jinshui District, Zhengzhou, 450000, Henan, China. wangyue0601@163.com.
Abstract
PURPOSE: To explore the clinical significance and mechanism of long noncoding RNA (lncRNA) HAGLROS in ovarian cancer. METHODS: The expression of HAGLROS in ovarian cancer was verified by online databases and quantitative reverse transcription polymerase chain reaction (qRT-PCR), and its relationship with clinicopathological parameters was analysed. Pearson correlation analysis was used to study the correlation between HAGLROS and miR-100 in ovarian cancer. Meta-analysis was used to explore the expression of miR-100 in ovarian cancer. In addition, we used bioinformatics to explore the target genes of miR-100 and perform functional analysis. RESULTS: HAGLROS was significantly upregulated in ovarian cancer (P < 0.001) and was closely related to disease stage (P = 0.033), tumour size (P = 0.032) and poor prognosis (P = 0.019). HAGLROS had a certain diagnostic value in ovarian cancer (area under the curve = 0.751). MiR-100 was negatively correlated with HAGLROS (r = 0.167, P = 0.001) and significantly downregulated in ovarian cancer. Bioinformatics analysis predicted a total of 31 potential target genes that interact with miR-100. These target genes were mainly involved in the regulation of cellular catabolic process, proteoglycan biosynthetic process and positive regulation of proteasomal ubiquitin-dependent protein catabolic process. Among them, mTOR and ZNRF2 are hub genes. CONCLUSION: HAGLROS is a potential biomarker for early diagnosis and prognosis evaluation of ovarian cancer. It can be used as a molecular sponge of miR-100 to regulate the expression of mTOR and ZNRF2 and affect the signal transduction of the mTOR pathway. HAGLROS is expected to be a new target for the treatment of ovarian cancer.
PURPOSE: To explore the clinical significance and mechanism of long noncoding RNA (lncRNA) HAGLROS in ovarian cancer. METHODS: The expression of HAGLROS in ovarian cancer was verified by online databases and quantitative reverse transcription polymerase chain reaction (qRT-PCR), and its relationship with clinicopathological parameters was analysed. Pearson correlation analysis was used to study the correlation between HAGLROS and miR-100 in ovarian cancer. Meta-analysis was used to explore the expression of miR-100 in ovarian cancer. In addition, we used bioinformatics to explore the target genes of miR-100 and perform functional analysis. RESULTS:HAGLROS was significantly upregulated in ovarian cancer (P < 0.001) and was closely related to disease stage (P = 0.033), tumour size (P = 0.032) and poor prognosis (P = 0.019). HAGLROS had a certain diagnostic value in ovarian cancer (area under the curve = 0.751). MiR-100 was negatively correlated with HAGLROS (r = 0.167, P = 0.001) and significantly downregulated in ovarian cancer. Bioinformatics analysis predicted a total of 31 potential target genes that interact with miR-100. These target genes were mainly involved in the regulation of cellular catabolic process, proteoglycan biosynthetic process and positive regulation of proteasomal ubiquitin-dependent protein catabolic process. Among them, mTOR and ZNRF2 are hub genes. CONCLUSION:HAGLROS is a potential biomarker for early diagnosis and prognosis evaluation of ovarian cancer. It can be used as a molecular sponge of miR-100 to regulate the expression of mTOR and ZNRF2 and affect the signal transduction of the mTOR pathway. HAGLROS is expected to be a new target for the treatment of ovarian cancer.
Authors: Eleonora A Braga; Marina V Fridman; Alexey A Moscovtsev; Elena A Filippova; Alexey A Dmitriev; Nikolay E Kushlinskii Journal: Int J Mol Sci Date: 2020-11-23 Impact factor: 5.923